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Relation extraction from arabic wikipedia

مؤلف البحث
Gehad Zakria, Mamdouh Farouk, Khaled Fathy, Malak N Makar
تاريخ البحث
مجلة البحث
Indian Journal of Science and Technology
المشارك في البحث
عدد البحث
Volume 12, Issue 46
موقع البحث
https://scholar.google.com/scholar?oi=bibs&cluster=16981496231598000900&btnI=1&hl=en
سنة البحث
2019
صفحات البحث
01-06
ملخص البحث

Objectives/Methods

This study aims to extract relations between entities from Arabic text. RelationExtraction is one of the most important tasks in text mining. Relation extraction is considered as a main step for many applications such as extracting triples from the text, Question Answering and Ontology building. However, extracting relations from the Arabic text is a difficult task compared to English due to lack of annotated Arabic corpora. This paper proposes a method for extracting relations from Arabic text based on ArabicWikipedia articles characteristics. The propose system extracts sentences that contain principle entity, secondary entity and relation from Wikipedia article, then we use WordNet and DBpedia to build the training set. Finally Naive Bayes Classifier is used to train and test the datasets.

Finding

There are few works to extract relations from Arabic text. These works depend on classification, clustering and rule based.

Application/improvement

The experiments show the effectiveness of the proposed approach which achieves high precision with 89% for classifying 19 type of semantic relations.